Manager, Quantitative Analysis - Model Risk Office

About This Role

Managing a Model Validation team within the Model Risk Office is the core of this role, focusing on ensuring the accuracy and robustness of the firm’s market risk models. This position is responsible for validating models, specifically those used for derivative pricing and risk management, including derivative valuation, market risk, and counterparty risk models. The role suits a quantitative analyst with strong communication skills to engage with diverse stakeholders.

Responsibilities

• Remain on the leading edge of analytical technology with a passion for the newest and most innovative tools
• Develop model approaches to assess model design and advance future capabilities
• Understand relevant business processes and portfolios associated with model use
• Understand technical issues in econometric, statistical, and machine learning modeling and apply these skills toward developing models and assessing model risks and opportunities
• Communicate technical subject matter clearly and concisely to individuals from various backgrounds both verbally and through written communication
• Prepare presentations of complex technical concepts and research results to non-specialist audiences and senior management
• Maintain the efficiency and accuracy of our models through continuous improvement and application of best practices
• Develop and maintain high quality and transparent documentation
• Leverage the latest open source technologies and tools to identify areas of opportunity in our existing framework

Requirements

• Demonstrated track-record in modeling and experience utilizing model estimation tools such as Python or R
• Ability to clearly communicate modeling results to management, model risk office, regulator and other modelers
• Drive to continuously improve all aspects of their work in a collaborative fashion
• Experience in machine learning
• Strong communication skills with the ability to quickly understand existing models and new requirements/business needs
• Experience working with Agile development methodologies
• Strong grasp of econometric theory and methodologies
• Desire to remain on the leading edge of analytical technology with a passion for the newest and most innovative tools
• Experience working with CCAR regulatory requirements
• Experience with derivative modeling
• Currently has, or is in the process of obtaining one of the following with an exception that the required degree will be obtained on or before the scheduled start date:
• A Master’s degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration plus 4 years of experience in quantitative analytics
• A PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 1 year of experience in quantitative analytics
• At least 4 years of experience in each of the following skills through education or experience:
• Statistical or econometric modeling
• Linear and logistic regression
• Programming in R, Python, or SQL
• Presenting statistical concepts and research results to non-statistical audience
• At least 4 years of experience in at least 3 of the following skills:
• Survival analysis modeling
• Time-series analysis
• Panel data (longitudinal data or cross-sectional time-series data) analysis
• Cross-sectional data analysis
• Machine learning
• Analysis and management of large datasets (>1M records)

Nice to have:

• 5 years of experience with Python, R or other statistical analyst software
• 5 years of experience in statistical modeling or regression analytics or machine learning
• At least 2 years of experience in derivative modeling (Fixed income, Commodity, FX or CDS)

Benefits

• Comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being

Important Details

• Locations: New York, NY; other locations subject to pay range associated with that location
• Capital One will consider sponsoring a new qualified applicant for employment authorization for this position

About the Company

At Capital One, data is at the center of everything. As a startup, the company disrupted the credit card industry by individually personalizing every credit card offer using statistical modeling and the relational database. This innovation and passion for data has led it to become a Fortune 200 company and a leader in data-driven decision-making, using cloud computing and machine learning technologies across billions of customer records to help everyday people save money, time and agony in their financial lives.